After two years in the Lab, Scott has decided to join the well paid workforce. Scott is a wonderful colleague to all of us and has made important contributions to our team. Thank you and best of lucks, Scott 🍀🍀🍀
Also thank you, Wenndy, for organizing and buying the present for Scott.
Keep in mind that significant associations shown here do not imply causality. That said, given that PrediXcan is seeking to test the role of gene expression variation on traits and we and others have shown that significant PrediXcan genes are enriched in causal genes, these results should be useful to delve into the mechanisms underlying gene to phenotype associations. False positives can arise because of several factors LD contamination By computing the probability of LD contamination, we try to reduce false positives due to LD rather than genuine colocalization of trait and expression causal variants.
PrediXcan and other transcriptome wide association study (TWAS) methods discover and prioritize genes based on a functional mechanism –regulation of gene expression. We agree that we have to temper over-enthusiasm, but Wainberg et al’s paper could represent a backlash to the enthusiasm that the community has for this approach, which we believe is well placed. Below are our responses to some of the statements of the paper. PrediXcan/TWAS associations do not imply causality
Most GWAS and eQTL studies have been performed in European samples. So how well do models trained in Europeans translate to other populations? Segal et al have shown that predictions of gene expression levels are robust across populations (link) The following figure shows the p-value of the correlation between predicted and observed expression levels in European and African samples from the 1000 Genomes set (GEUVADIS RNA-seq) using model trained in GTEx with majority European individuals.
Update (11/1/2017) Gene level results “meta analyzed” across tissues now available. Shinyapp to directly query by gene and phenotype is here but can be slow. Stay tuned for faster version coming soon. As many of you may know, Neale Lab made a big splash in the GWAS community by releasing the summary results of 2400+ phenotypes from the UK Biobank. Following their lead on open science and open data sharing, we are releasing the bulk runs of PrediXcan association based on Neale Lab’s UKB results and 44 tissues models from GTEx V6p release.
We are delighted to be awarded NIH Cloud Credit that will help us fund our cloud-based web applications and databases and broadly share our tools and resources.
Thank you, Jiamao, for pushing this through 👍😃
Information about Cloud Credits here
So et al use S-PrediXcan to find psychiatric drug repositioning candidates.
After the last formal GTEx analysis working group’s internal meeting at Rockville, MD, the Im Lab went for dinner with Nancy Cox, Barbara Stranger, and Eric Gamazon. From left to right: Rodrigo, Milton, Jiamao, Barbara, Nancy, Eric, Haky, Scott, and Alvaro. Great French dishes with Asian influence.